Computationally feasible VCG mechanisms
Proceedings of the 2nd ACM conference on Electronic commerce
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
An approximate truthful mechanism for combinatorial auctions with single parameter agents
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Computing best-response strategies in infinite games of incomplete information
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Combinatorial Auctions
Empirical mechanism design: methods, with application to a supply-chain scenario
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Optimal decision-making with minimal waste: strategyproof redistribution of VCG payments
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Stochastic search methods for nash equilibrium approximation in simulation-based games
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Achieving budget-balance with Vickrey-based payment schemes in exchanges
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Approximately-strategyproof and tractable multiunit auctions
Decision Support Systems - Special issue: The fourth ACM conference on electronic commerce
Complexity of mechanism design
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
False-name bidding in first-price combinatorial auctions with incomplete information
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Payment rules through discriminant-based classifiers
Proceedings of the 13th ACM Conference on Electronic Commerce
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Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties such as budget-balance, stability against deviations by coalitions, and computational tractability. In the search for maximally-strategyproof mechanisms that simultaneously satisfy other desirable properties, we introduce a new metric to quantify the strategyproofness of a mechanism, based on comparing the payoff distribution, given truthful reports, against that of a strategyproof "reference" mechanism that solves a problem relaxation. Focusing on combinatorial exchanges, we demonstrate that the metric is informative about the eventual equilibrium, where simple regret-based metrics are not, and can be used for online selection of an effective mechanism.